R1SVM: A randomised nonlinear approach to large-scale anomaly detection

The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Ratios of T-cell immune-effectors with tumour associated macrophages and PD-1/PD-L1 axis immune-checkpoint molecules, as prognosticators in diffuse large B cell lymphoma: A population-based study

Background Risk-stratification of diffuse large B-cell lymphoma (DLBCL) requires identification of patients with disease that is not cured despite initial R-CHOP. Although the prognostic importance of the tumour microenvironment (TME) is established, the optimal strategy to quantify it is unknown. Methods The relationship between immune-effector and inhibitory (checkpoint) genes was assessed by NanoString™ in 252 paraffin-embedded DLBCL tissues. A model to quantify net anti-tumoural immunity as an outcome predictor was tested in 158 R-CHOP treated patients, and validated in tissue/blood from two independent R-CHOP treated cohorts of 233 and 140 patients respectively. Findings T and NK-cell immune-effector molecule expression correlated with tumour associated macrophage and PD-1/PD-L1 axis markers consistent with malignant B-cells triggering a dynamic checkpoint response to adapt to and evade immune-surveillance. A tree-based survival model was performed to test if immune-effector to checkpoint ratios were prognostic. The CD4*CD8:(CD163/CD68)*PD-L1 ratio was better able to stratify overall survival than any single or combination of immune markers, distinguishing groups with disparate 4-year survivals (92% versus 47%). The immune ratio was independent of and added to the revised international prognostic index (R-IPI) and cell-of-origin (COO). Tissue findings were validated in 233 DLBCL R-CHOP treated patients. Furthermore, within the blood of 140 R-CHOP treated patients immune-effector:checkpoint ratios were associated with differential interim-PET/CT+ve/-ve expression.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Shrinking Violets

Description of the work Shrinking Violets is comprised of two half scale garments in laser cut silk organza, developed with a knotting device to allow for disassembly and reassembly. The first is a jacket in layered red organza including black storm flap details. The second is a vest in jade organza with circles of pink organza attached through a pattern of knots. Research Background This practice-led fashion design research sits within the field of Design for Sustainability (DfS) in fashion that seeks to mitigate the environmental and ethical impacts of fashion consumption and production. The research explores new systems of garment construction for DfS, and examines how these systems may involve ‘designing’ new user interactions with the garments. The garments’ construction system allows them to be disassembled and recycled or reassembled by users to form a new garment. Conventional garment design follows a set process of cutting and construction, with pattern pieces permanently machine-stitched together. Garments typically contain multiple fibre types; for example a jacket may be constructed from a shell of wool/polyester, an acetate lining, fusible interlinings, and plastic buttons. These complex inputs mean that textile recycling is highly labour intensive, first to separate the garment pieces and second to sort the multiple fibre types. This difficulty results in poor quality ‘shoddy’ comprised of many fibre types and unsuitable for new apparel, or in large quantities of recyclable textile waste sent to landfill (Hawley 2011). Design-led approaches that consider the garment’s end of life in the design process are a way of addressing this problem. In Gulich’s (2006) analysis, use of single materials is the most effective way to ensure ease of recycling, with multiple materials that can be detached next in effectiveness. Given the low rate of technological innovation in most apparel manufacturing (Ruiz 2011), a challenge for effective recycling is how to develop new manufacturing methods that allow for garments to be more easily disassembled at end-of-life. Research Contribution This project addresses the research question: How can design for disassembly be considered within the fashion design process? I have employed a practice-led methodology in which my design process leads the research, making use of methods of fashion design practice including garment and construction research, fabric and colour research, textile experimentation, drape, patternmaking, and illustration as well as more recent methods such as laser cutting. Interrogating the traditional approaches to garment construction is necessarily a technical process; however fashion design is as much about the aesthetic and desirability of a garment as it is about the garment’s pragmatics or utility. This requires a balance between the technical demands of designing for disassembly with the aesthetic demands of fashion. This led to the selection of luxurious, semi-transparent fabrics in bold floral colours that could be layered to create multiple visual effects, as well as the experimentation with laser cutting for new forms of finishing and fastening the fabrics together. Shrinking Violets makes two contributions to new knowledge in the area of design for sustainability within fashion. The first is in the technical development of apparel modularity through the system of laser cut holes and knots that also become a patterning device. The second contribution lies in the design of a system for users to engage with the garment through its ability to be easily reconstructed into a new form. Research Significance Shrinking Violets was exhibited at the State Library of Queensland’s Asia Pacific Design Library, 1-5 November 2015, as part of The International Association of Societies of Design Research’s (IASDR) biannual design conference. The work was chosen for display by a panel of experts, based on the criteria of design innovation and contribution to new knowledge in design. References Gulich, B. (2006). Designing textile products that are easy to recycle. In Y. Wang (Ed.), Recycling in Textiles (pp. 25-37). London: Woodhead. Hawley, J. M. (2011). Textile recycling options: exploring what could be. In A. Gwilt & T. Rissanen (Eds.), Shaping Sustainable Fashion: Changing the way we make and use clothes (pp. 143 - 155). London: Earthscan. Ruiz, B. (2014). Global Apparel Manufacturing. Retrieved 10 August 2014, from http://clients1.ibisworld.com/reports/gl/industry/default.aspx?entid=470

Modulatory roles of microRNAs in the regulation of different signalling pathways in large bowel cancer stem cells

There are emerging data to suggest that microRNAs (miRNAs) have significant roles in regulating the function of normal cells and cancer stem cells (CSCs). This review aims to analyse the roles of miRNAs in the regulation of colon CSCs through their interaction with various signalling pathways. Studies showed a large number of miRNAs that are reported to be deregulated in colon CSCs. However, few of the studies available were able to outline the function of miRNAs in colon CSCs and uncover their signalling pathways. From those miRNAs, which are better described, miR-21 followed by miR-34, miR-200 and miR-215 are the most reported miRNAs to have roles in colon CSC regulation. In particular, miRNAs have been reported to regulate the stemness features of colon CSCs mainly via Wnt/B-catenin and Notch signalling pathways. Additionally, miRNAs have been reported to act on processes involving CSCs through cell cycle regulation genes and epithelial-mesenchymal transition. The relative paucity of data available on the significance of miRNAs in CSCs means that new studies will be of great importance to determine their roles and to identify the signalling pathways through which they operate. Such studies may in future guide further research to target these genes for more effective cancer treatment. miRNAs were shown to regulate the function of cancer stem cells in large bowel cancer by targeting a few key signalling pathways in cells.

Additively manufactured device for dynamic culture of large arrays of 3D tissue engineered constructs

The ability to test large arrays of cell and biomaterial combinations in 3D environments is still rather limited in the context of tissue engineering and regenerative medicine. This limitation can be generally addressed by employing highly automated and reproducible methodologies. This study reports on the development of a highly versatile and upscalable method based on additive manufacturing for the fabrication of arrays of scaffolds, which are enclosed into individualized perfusion chambers. Devices containing eight scaffolds and their corresponding bioreactor chambers are simultaneously fabricated utilizing a dual extrusion additive manufacturing system. To demonstrate the versatility of the concept, the scaffolds, while enclosed into the device, are subsequently surface-coated with a biomimetic calcium phosphate layer by perfusion with simulated body fluid solution. 96 scaffolds are simultaneously seeded and cultured with human osteoblasts under highly controlled bidirectional perfusion dynamic conditions over 4 weeks. Both coated and noncoated resulting scaffolds show homogeneous cell distribution and high cell viability throughout the 4 weeks culture period and CaP-coated scaffolds result in a significantly increased cell number. The methodology developed in this work exemplifies the applicability of additive manufacturing as a tool for further automation of studies in the field of tissue engineering and regenerative medicine.

Assessment of code bias variations of BDS triple-frequency signals and their impacts on ambiguity resolution for long baselines

Carrier phase ambiguity resolution over long baselines is challenging in BDS data processing. This is partially due to the variations of the hardware biases in BDS code signals and its dependence on elevation angles. We present an assessment of satellite-induced code bias variations in BDS triple-frequency signals and the ambiguity resolutions procedures involving both geometry-free and geometry-based models. First, since the elevation of a GEO satellite remains unchanged, we propose to model the single-differenced fractional cycle bias with widespread ground stations. Second, the effects of code bias variations induced by GEO, IGSO and MEO satellites on ambiguity resolution of extra-wide-lane, wide-lane and narrow-lane combinations are analyzed. Third, together with the IGSO and MEO code bias variations models, the effects of code bias variations on ambiguity resolution are examined using 30-day data collected over the baselines ranging from 500 to 2600 km in 2014. The results suggest that although the effect of code bias variations on the extra-wide-lane integer solution is almost ignorable due to its long wavelength, the wide-lane integer solutions are rather sensitive to the code bias variations. Wide-lane ambiguity resolution success rates are evidently improved when code bias variations are corrected. However, the improvement of narrow-lane ambiguity resolution is not obvious since it is based on geometry-based model and there is only an indirect impact on the narrow-lane ambiguity solutions.

The importance of context in engaging students large first year management classes: A case study

Engaging large first year classes in tertiary education poses a number of significant challenges, most of which have been discussed by others. One area that has not received the kind of attention that it warrants is the context within which the engagement activities take place. This paper examines both the processes used to engage a large first year management class in a major city university and how the context of the classes shaped activities and student responses to these activities. It was recognised that students had certain types of learning styles, but given the total number of students (in excess of 1200) it was realised that is would be impossible to cater to all possibilities. A key outcome of the exercise was the importance of context in shaping student behaviours.

When and why threats go undetected: Impacts of event rate and shift length on threat detection accuracy during airport baggage screening

Objective: We aimed to assess the impact of task demands and individual characteristics on threat detection in baggage screeners. Background: Airport security staff work under time constraints to ensure optimal threat detection. Understanding the impact of individual characteristics and task demands on performance is vital to ensure accurate threat detection. Method: We examined threat detection in baggage screeners as a function of event rate (i.e., number of bags per minute) and time on task across 4 months. We measured performance in terms of the accuracy of detection of Fictitious Threat Items (FTIs) randomly superimposed on X-ray images of real passenger bags. Results: Analyses of the percentage of correct FTI identifications (hits) show that longer shifts with high baggage throughput result in worse threat detection. Importantly, these significant performance decrements emerge within the first 10 min of these busy screening shifts only. Conclusion: Longer shift lengths, especially when combined with high baggage throughput, increase the likelihood that threats go undetected. Application: Shorter shift rotations, although perhaps difficult to implement during busy screening periods, would ensure more consistently high vigilance in baggage screeners and, therefore, optimal threat detection and passenger safety.

Heritability analysis of surface-based cortical thickness estimation on a large twin cohort

The aim of this paper is to assess the heritability of cerebral cortex, based on measurements of grey matter (GM) thickness derived from structural MR images (sMRI). With data acquired from a large twin cohort (328 subjects), an automated method was used to estimate the cortical thickness, and EM-ICP surface registration algorithm was used to establish the correspondence of cortex across the population. An ACE model was then employed to compute the heritability of cortical thickness. Heritable cortical thickness measures various cortical regions, especially in frontal and parietal lobes, such as bilateral postcentral gyri, superior occipital gyri, superior parietal gyri, precuneus, the orbital part of the right frontal gyrus, right medial superior frontal gyrus, right middle occipital gyrus, right paracentral lobule, left precentral gyrus, and left dorsolateral superior frontal gyrus.

Minimising lateral impact derailment potential at level crossings through guard rails

Derailments due to lateral collisions between heavy road vehicles and passenger trains at level crossings (LCs) are serious safety issues. A variety of countermeasures in terms of traffic laws, communication technology and warning devices are used for minimising LC accidents; however, innovative civil infrastructure solution is rare. This paper presents a study of the efficacy of guard rail system (GRS) to minimise the derailment potential of trains laterally collided by heavy road vehicles at LCs. For this purpose, a three-dimensional dynamic model of a passenger train running on a ballasted track fitted with guard rail subject to lateral impact caused by a road truck is formulated. This model is capable of predicting the lateral collision-induced derailments with and without GRS. Based on dynamic simulations, derailment prevention mechanism of the GRS is illustrated. Sensitivities of key parameters of the GRS, such as the flange way width, the installation height and contact friction, to the efficacy of GRS are reported. It is shown that guard rails can enhance derailment safety against lateral impacts at LCs.

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

A semi-analytical solution for multilayer diffusion in a composite medium consisting of a large number of layers

Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.

Australian fly-in, fly-out operations: Impacts on communities, safety workers and their families

Background Australia’s mineral, resource and infrastructure sectors continues to expand as operations in rural and remote locations increasingly rely on fly-in, fly-out or drive-in, drive-out workforces in order to become economically competitive. The issues in employing these workforces are becoming more apparent and include a range of physical, mental, psychosocial, safety and community challenges. Objectives This review aims to consolidate a range of research conducted to communicate potential challenges for industry in relation to a wide variety of issues when engaging and using FIFO/DIDO workforces which includes roster design, working hours, fatigue, safety performance, employee wellbeing, turnover, psychosocial relationships and community concerns. Methods A wide literature review was performed using EBSCOhost and Google Scholar, with a focus on FIFO or DIDO workforces engaged within the resources sector. Results A number of existing gaps in the management of FIFO workforces and potential for future research were identified. This included the identification of various roster designs and hours worked across the resources industry and how to best understand the influences of roster swings, and work hours on fatigue, safety, psychological wellbeing and job satisfaction. Fatigue management, particularly in relation to travelling after extended work shifts can increase the risk for road safety and influence safety performance while at work due to a culmination of long hours, roster cycle and accumulated sleep debt. Further challenges associated with the engagement of this workforce include feelings of isolation, physiological and general health and lifestyle concerns. Conclusions FIFO workforces appear to be at an increased risk physically and mentally due to a wide range of influences of this unique lifestyle, particularly in relation to rosters, length of shift and feelings of community disengagement. Research and data collected has been limited in understanding the influences on employee engagement, satisfaction, retention and safety. Ensuring the challenges associated with FIFO employment are understood, addressed and communicated to workers and their families may assist.